NF2 Loss Promotes Oncogenic RAS-Induced Thyroid Cancers via YAP-Dependent Transactivation of RAS Proteins and Sensitizes Them to MEK Inhibition

Genomic Alterations of Anaplastic Thyroid Carcinoma Detected by Targeted Massive Parallel Sequencing in a BRAF(V600E) Mutation-Prevalent Area

BACKGROUND

Anaplastic thyroid carcinoma (ATC), the most aggressive type of thyroid cancer, has no effective therapy. Due to its dismal prognosis, it is vital to understand the genetic alterations of ATC and identify effective molecular targets. Targeted next-generation sequencing was performed to investigate the mutational profile of ATC using a massive parallel sequencing approach.

METHODS

DNA from formalin-fixed, paraffin-embedded archival samples of 11 ATCs and normal matched pairs were used. A total of 48 genetic alterations were identified by targeted exome sequencing. These alterations were validated by mass spectrometric genotyping and direct Sanger sequencing.

RESULTS

The most commonly mutated gene was BRAF, identified in 10 samples (91%), all showing the V600E point mutation. A KRAS point mutation was observed in the one sample (9%) without the BRAF(V600E) mutation. All 11 ATCs harbored BRAF or RAS mutations, reflecting the possibility that differentiated thyroid carcinomas progress to ATCs after the accumulation of mutations. A loss of function mutation of TP53 was observed in eight samples (73%), a PIK3CA mutation was observed in two samples (18%), and a frameshift mutation of PTEN was observed in one sample (9%). Twenty-eight novel mutated genes were found that had not previously been associated with ATC. Of these, loss of function mutations of NF2, KMT2D, and PKHD1 were repeatedly seen in three samples (27%), two samples (18%), and two samples (18%), respectively. Using direct Sanger sequencing, two samples (18%) were also found with a RASAL1 mutation. KMT2D and RASAL1 mutations were significantly associated with shorter ATC patient survival.

CONCLUSIONS

This comprehensive analysis of ATCs using targeted massive parallel sequencing identified several novel mutations in ATCs, such as loss of function mutations of NF2 or KMT2D. Future studies are needed to confirm the role of these novel mutations as independent drivers of ATC development.

Genomic and transcriptomic hallmarks of poorly differentiated and anaplastic thyroid cancers

BACKGROUND

Poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) are rare and frequently lethal tumors that so far have not been subjected to comprehensive genetic characterization.

METHODS

We performed next-generation sequencing of 341 cancer genes from 117 patient-derived PDTCs and ATCs and analyzed the transcriptome of a representative subset of 37 tumors. Results were analyzed in the context of The Cancer Genome Atlas study (TCGA study) of papillary thyroid cancers (PTC).

RESULTS

Compared to PDTCs, ATCs had a greater mutation burden, including a higher frequency of mutations in TP53, TERT promoter, PI3K/AKT/mTOR pathway effectors, SWI/SNF subunits, and histone methyltransferases. BRAF and RAS were the predominant drivers and dictated distinct tropism for nodal versus distant metastases in PDTC. RAS and BRAF sharply distinguished between PDTCs defined by the Turin (PDTC-Turin) versus MSKCC (PDTC-MSK) criteria, respectively. Mutations of EIF1AX, a component of the translational preinitiation complex, were markedly enriched in PDTCs and ATCs and had a striking pattern of co-occurrence with RAS mutations. While TERT promoter mutations were rare and subclonal in PTCs, they were clonal and highly prevalent in advanced cancers. Application of the TCGA-derived BRAF-RAS score (a measure of MAPK transcriptional output) revealed a preserved relationship with BRAF/RAS mutation in PDTCs, whereas ATCs were BRAF-like irrespective of driver mutation.

CONCLUSIONS

These data support a model of tumorigenesis whereby PDTCs and ATCs arise from well-differentiated tumors through the accumulation of key additional genetic abnormalities, many of which have prognostic and possible therapeutic relevance. The widespread genomic disruptions in ATC compared with PDTC underscore their greater virulence and higher mortality.

FUNDING

This work was supported in part by NIH grants CA50706, CA72597, P50-CA72012, P30-CA008748, and 5T32-CA160001; the Lefkovsky Family Foundation; the Society of Memorial Sloan Kettering; the Byrne fund; and Cycle for Survival.

An integrated transcriptomic and computational analysis for biomarker identification in human glioma

Malignant glioma is one of the most common primary brain tumors and is among the deadliest of human cancers. The molecular mechanism for human glioma is poorly understood. Early prognosis of this disease and early treatment are vital. Thus, it is crucial to target the key genes controlling pathogenesis in the early stage of glioma. In this study, differentially expressed genes in human glioma and paired peritumoral tissues were detected by transcriptome microarray analysis. Following gene microarray analysis, the gene expression profile in the differential grade glioma was further validated by bioinformatic analyses, co-expression network construction. Microarray analysis revealed that 1725 genes were differentially expressed and classified into different glioma stage. The analysis revealed 14 genes that were significantly associated with survival with a false discovery rate. Among these genes, macrophage capping protein (CAPG), a member of the actin-regulatory protein, was the key gene in a 20-gene network that modulates cell motility by interacting with the cytoskeleton. Furthermore, the prognostic impact of CAPG was validated by use of quantitative real-time polymerase chain reaction (qPCR) and immunohistochemistry on human glioma tissue. CAPG protein was significantly upregulated in clinical high-grade glioblastoma as compared with normal brain tissues. Overexpression of CAPG levels also predict shorter overall survival of glioma patients. These data demonstrated CAPG protein expression in human glioma was associated with tumorigenesis and may be a biomarker for identification of the pathological grade of glioma.